In recent years, inventory management has gained importance, particularly due to the challenges posed by the COVID-19 pandemic, which led to significant material shortages in supply chains. In times when companies are forced to maintain low inventory levels, high inventory accuracy becomes even more critical to ensure process reliability in production and to avoid disruptions. However, this is precisely where the problem of inventory discrepancies often arises. These discrepancies between physical and system inventories can lead to severe consequences, such as production shutdowns. For these reasons, the purpose of this thesis is to conduct a comprehensive cause analysis of inventory discrepancies in order to formulate targeted recommendations to improve inventory accuracy. Initially, the concept of inventory management will be explored, and potential causes of inventory discrepancies will be explained. In particular, inventory as an area of responsibility for inventory management , will be discussed in more detail. Hence, the fundaments of ERP systems, especially in the context of SAP, will be examined, including the historical development and typical characteristics. This section will also consider innovative solutions that could be systemically applied to enhance inventory accuracy. Furthermore, risk management methods suitable for cause analysis of inventory discrepancies will be outlined. Finally, a thorough cause analysis will be conducted based on a practical example. To adress the research questions, a comprehensive literature review was conducted initially. Primarily, the library search engine PRIMO of the University of Applied Sciences Upper Austria, as well as Google Scholar and Wiley, were utilized as research sources. Additionally, an interview with an internal specialist from the BMW Group plant in Steyr was conducted as part of the application example. The results of the practical example at the BMW Group plant in Steyr highlight that numerous factors influence inventory levels and can lead to discrepancies. Particularly notable is the human factor, which plays a significant role in the emergence of deviations. Other contributing factors include IT systems, supplier, and internal areas such as physical logistics and engine assembly. The use of innovative technologies like artificial intelligence and RFID can improve inventory accuracy and should therefore be considered. Additionally, prioritizing and frequently monitoring relevant materials that often experience discrepancies can be beneficial.
Date of Award | 2024 |
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Original language | German (Austria) |
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Supervisor | Matthias Schmidt (Supervisor) |
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Bestandsdifferenzen in der Logistik: Ursachen, Risiken und Vermeidungspotenziale
Hochwallner, V. (Author). 2024
Student thesis: Bachelor's Thesis